Klaus-Tschira-Institute for Computational Cardiology -
Bioinformatics and Systems Cardiology
Post-transcriptional network analysis is one necessary building block to advance our understanding of cardiovascular health and disease. It will open up new medical options.
The flow of genetic information from DNA to proteins has been traditionally seen as a linear pathway with an RNA intermediate. However, instead of just being an inert carrier of information, RNA performs a multitude of tasks and may even be transformed in the course of these events. For example, mRNA stability and translation efficiency is regulated by secondary structure and/or interactions with microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and RNA binding proteins (RBPs). Moreover, RNA editing modifies the primary sequence, and changes in RNA localization influence the availability of RNA molecules. The rediscovery of circular RNAs (circRNAs) added another poorly characterized class of molecules to the set of players. All of these processes and interaction networks are subsumed under the term “post-transcriptional gene regulation” and have an impact on numerous cellular processes.
The Dieterich Lab works on computational and statistical approaches to study
- RNA modifications (i.e. RNA editing and others)
- RNA-RNA and RNA-protein interactions
- Circular RNAs
- Control of translation
- RNA dynamics
- Data integration (OMICS & clinical data)
Typically, specific questions or observations from biology and medicine are at the beginning of our work. A possible question could be:
"Cardiac muscle cells grow both through fitness training and through diseased influences, for example hypertension. Why, however, are the long-term effects on the molecular and medical level significantly different? "
As a rule, we create hypotheses together with our experimental partners, which we subsequently examine by established bioinformatic and statistical methods, as well as by self-developed software and procedures. Newly developed software tools are made available to the broad scientific community, constantly developed and improved. Quantitative system biology and medicine are characterized by immense amounts of data which are no longer manageable on ordinary workplace calculators. For this purpose, the Bioinformatics and System Cardiology Group has its own network of several dozen high-performance computers, which can also evaluate extensive experimental data in a short time. A success criterion of our work is the constant and intensive contact to biologists and physicians so that at the end of our analyzes understandable and verifiable results stand.